PROJECT SUMMARY Sensitive and non-invasive detection of changes in brain structure or function provides more means to diagnose, monitor, prevent or delay the progression of diseases. Recently, longitudinal magnetic resonance imaging (MRI) has been applied to large neuroimaging studies of Alzheimer?s disease (AD) and traumatic brain injury (TBI) to track brain changes over time. Diffusion-weighted MRI (dMRI) is commonly used to measure the physical properties of white matter (WM) of the brain. WM is mainly made up of nerve fibers that act as a relay and coordinate communication between different brain regions, and exhibits changes in shape and diffusion of water molecules across the life span. However, conventional dMRI analysis methods have failed to properly consider shape change in brain tissue, limiting the detection of small WM changes and investigation of its clinical significance. To address limitations of current MRI analysis approaches, in this project, we will model complex WM damage patterns on a biomechanical framework using multi-modality MRI acquired from ongoing longitudinal TBI cohorts of youth football players (funded by current NINDS R01s but not processed using the proposed methods). Our scientific hypotheses are that (a) participation in a season of contact sports is associated with WM changes and the degree of change is correlated with accumulated head impact or clinical symptoms and cognitive change, and that (b) the WM changes along the fiber pathway estimated from the proposed biomechanical approach will improve statistical power in detecting abnormal WM changes compared to conventional diffusion MRI measures. To test the hypotheses, we propose two Specific Aims: (1) To model white matter damages along the pathway of fibers in youth football players: We will identify abnormal brain development patterns in youth football players who experienced repetitive subconcussive head impacts during a season of play compared to normal non- contact sports players. New MRI measures derived from the proposed method will be correlated with head impact exposure. (2) To validate the clinical utility of the new white matter modeling approach: Correlation analyses between MRI measures and post-traumatic cognitive/symptom measures will be conducted to determine whether these new MRI measures demonstrate higher statistical power in detecting abnormal WM changes. Through the Specific Aims proposed above, we will explain the underlying brain injury mechanisms of repetitive head impacts even in the absence of diagnosed concussion. This novel approach promises to develop valuable new tools with the potential to broadly impact the medical care of contact sports players and early AD adults by addressing more natural and realistic changes of WM on a biomechanical framework. All source codes related to the proposed analyses will be well documented and available at software sharing platforms for users to apply the method to various MRI studies on white matter diseases.